Package: PRC 0.2.2

PRC: Principal Response Curves (PRC) For Displaying Multivariate Main Effects And Interactions

PRC is a small \code{vegan}-based package to create and display Principal Response Curves (PRC), which are a special case of Redundancy Analysis (rda) for multivariate responses in designed experiments and repeated measurement designs. PRC expresses ordination scores as deviation from a reference, usually to visualize multivariate A-dependent effects (e.g time-dependent effects) of a treatment B in (un)balanced factorial experiments. The main user functions are \code{\link{doPRC}}, \code{\link{plotPRC}} and \code{\link{plotPRC2d}}. The easiest example is the code demo \code{PRC_pyrifos}.

Authors:Cajo J.F ter Braak [aut, cre]

PRC_0.2.2.tar.gz
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PRC_0.2.2.tgz(r-4.4-any)PRC_0.2.2.tgz(r-4.3-any)
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PRC.pdf |PRC.html
PRC/json (API)

# Install 'PRC' in R:
install.packages('PRC', repos = c('https://cajoterbraak.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/cajoterbraak/prc/issues

Datasets:

On CRAN:

2.04 score 11 scripts 10 exports 40 dependencies

Last updated 10 months agofrom:4461bebecd. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winWARNINGOct 31 2024
R-4.5-linuxWARNINGOct 31 2024
R-4.4-winWARNINGOct 31 2024
R-4.4-macWARNINGOct 31 2024
R-4.3-winWARNINGOct 31 2024
R-4.3-macWARNINGOct 31 2024

Exports:doPRCfvalues4levelsget_focal_and_conditioning_factorsplot_sample_scores_cdtplot_species_scores_2dplot_species_scores_bkplotPRCplotPRC2dPRC_scoresrdacca_taxon_stats

Dependencies:cliclustercolorspacedplyrfansifarvergenericsggplot2ggrepelgluegridExtragtableisobandlabelinglatex2explatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepermutepillarpkgconfigR6RColorBrewerRcpprlangscalesstringistringrtibbletidyselectutf8vctrsveganviridisLitewithr